FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3202060937> ?p ?o ?g. }

• W3202060937 endingPage "115467" @default.
• W3202060937 startingPage "115467" @default.
• W3202060937 abstract "The saturated water flow phenomenon is determined by the soil pore transport processes occurring at a micro-scale. In this study, saturated water flow was modeled using two different approaches, depending on the existence of the percolating macropore network. The soil material comprised 26 undisturbed soil cores. Soil samples were scanned using an X-ray micro-CT scanner, and saturated hydraulic conductivity (Ksat), bulk density and particle size distribution were measured. The voxel size for X-ray CT scans of soil cores was 23.6 µm, which allowed soil macropore network discrimination. The macropore network was percolating in 11 samples, while the remaining cores were not. A typical approach based on Navier–Stokes (NS) equations was used for saturated water flow modeling in the case of a percolating samples. In the case of cores with a non-percolating macropore network, the NS modeling approach could not be used. An alternative method of modeling (NS/Darcy) was used in this case, blending: regular NS flow in the well-defined macropores with the Darcy–Forchheimer flow in the remaining part – the soil matrix. Soil matrix is treated by the NS/Darcy model as a pore medium without well-defined pore geometry but with some intrinsic permeability incorporated in the model using the Darcy–Forchheimer equation. Unlike the NS approach, the NS/Darcy model allowed for the simulation of water flow for all soil samples, including those where the macropore network was not percolating. Based on simulations, the Ksat was estimated used for model validation. The analysis of results leads to the proposal of a new hybrid modeling approach, mixing the NS and NS/Darcy modeling approaches. A good estimation of the Ksat was obtained using the proposed model (R2 = 0.61). The NS/Darcy modeling approach was used for the analysis of the macropore flow in the soil media. The simulations show that water permeates through the core, but macropores are a favorable flow path if they exist, even if they are not directly connected to each other. The areas of the soil cores taking part in the preferential, macropore flow were quantified, showing that only a small fraction of the macropores take part in water flow both for percolating and non-percolating cores. But generally, for most of the analyzed flow-related indices, apparent differences in results between percolating and non-percolating samples were observed. Effective flow area (EFA), i.e., the sample area used for water flow with a velocity higher than the threshold velocity (Utr) was analyzed. Considering the macropore flow, only ∼2% of sample volume is responsible for: 82% of the total flux in case of percolated and 34% in case of non-percolated samples. Also, for non-percolated samples, the dependence (R2 = 0.44) between relative flux participation and the effective flow area is observed. The simulation results for the non-percolating samples revealed the relationship between the simulated saturated conductivity of the whole soil sample and the saturated conductivity of the soil matrix and macroporosity. This allowed for developing a simple multiple linear regression model (R2 = 0.98) of the soil core’s hydraulic conductivity." @default.
• W3202060937 created "2021-10-11" @default.
• W3202060937 creator A5002346245 @default.
• W3202060937 creator A5004153682 @default.
• W3202060937 creator A5021911218 @default.
• W3202060937 creator A5045042614 @default.
• W3202060937 creator A5046139805 @default.
• W3202060937 creator A5062135617 @default.
• W3202060937 date "2022-01-01" @default.
• W3202060937 modified "2023-09-25" @default.
• W3202060937 title "Hybrid modelling of saturated water flow in percolating and non-percolating macroporous soil media" @default.
• W3202060937 cites W1547714734 @default.
• W3202060937 cites W1963489413 @default.
• W3202060937 cites W1965834911 @default.
• W3202060937 cites W1966882003 @default.
• W3202060937 cites W1967429908 @default.
• W3202060937 cites W1980447427 @default.
• W3202060937 cites W2008264575 @default.
• W3202060937 cites W2016087912 @default.
• W3202060937 cites W2016529415 @default.
• W3202060937 cites W2034731678 @default.
• W3202060937 cites W2048409756 @default.
• W3202060937 cites W2051931160 @default.
• W3202060937 cites W2064315215 @default.
• W3202060937 cites W2085904748 @default.
• W3202060937 cites W2128162681 @default.
• W3202060937 cites W2140718330 @default.
• W3202060937 cites W2167279371 @default.
• W3202060937 cites W2174429415 @default.
• W3202060937 cites W2212450312 @default.
• W3202060937 cites W2292085449 @default.
• W3202060937 cites W2466658767 @default.
• W3202060937 cites W2515771168 @default.
• W3202060937 cites W2528639730 @default.
• W3202060937 cites W2579928606 @default.
• W3202060937 cites W2610258053 @default.
• W3202060937 cites W2612996122 @default.
• W3202060937 cites W2614048849 @default.
• W3202060937 cites W2622403716 @default.
• W3202060937 cites W2743956972 @default.
• W3202060937 cites W2752492782 @default.
• W3202060937 cites W2763097094 @default.
• W3202060937 cites W2774011225 @default.
• W3202060937 cites W2778005555 @default.
• W3202060937 cites W2877678270 @default.
• W3202060937 cites W2899495193 @default.
• W3202060937 cites W2901376740 @default.
• W3202060937 cites W2913912251 @default.
• W3202060937 cites W2958588135 @default.
• W3202060937 cites W2981504905 @default.
• W3202060937 cites W3005359522 @default.
• W3202060937 cites W3011600985 @default.
• W3202060937 cites W3046516874 @default.
• W3202060937 cites W612655414 @default.
• W3202060937 doi "https://doi.org/10.1016/j.geoderma.2021.115467" @default.
• W3202060937 hasPublicationYear "2022" @default.
• W3202060937 type Work @default.
• W3202060937 sameAs 3202060937 @default.
• W3202060937 citedByCount "6" @default.
• W3202060937 countsByYear W32020609372022 @default.
• W3202060937 countsByYear W32020609372023 @default.
• W3202060937 crossrefType "journal-article" @default.
• W3202060937 hasAuthorship W3202060937A5002346245 @default.
• W3202060937 hasAuthorship W3202060937A5004153682 @default.
• W3202060937 hasAuthorship W3202060937A5021911218 @default.
• W3202060937 hasAuthorship W3202060937A5045042614 @default.
• W3202060937 hasAuthorship W3202060937A5046139805 @default.
• W3202060937 hasAuthorship W3202060937A5062135617 @default.
• W3202060937 hasBestOaLocation W32020609371 @default.
• W3202060937 hasConcept C103272765 @default.
• W3202060937 hasConcept C105569014 @default.
• W3202060937 hasConcept C120882062 @default.
• W3202060937 hasConcept C120991184 @default.
• W3202060937 hasConcept C121332964 @default.
• W3202060937 hasConcept C127313418 @default.
• W3202060937 hasConcept C159390177 @default.
• W3202060937 hasConcept C159750122 @default.
• W3202060937 hasConcept C161790260 @default.
• W3202060937 hasConcept C183447037 @default.
• W3202060937 hasConcept C185592680 @default.
• W3202060937 hasConcept C187320778 @default.
• W3202060937 hasConcept C192562407 @default.
• W3202060937 hasConcept C2988574769 @default.
• W3202060937 hasConcept C38349280 @default.
• W3202060937 hasConcept C41625074 @default.
• W3202060937 hasConcept C55493867 @default.
• W3202060937 hasConcept C57879066 @default.
• W3202060937 hasConcept C57924286 @default.
• W3202060937 hasConcept C63184880 @default.
• W3202060937 hasConcept C6648577 @default.
• W3202060937 hasConcept C82776694 @default.
• W3202060937 hasConceptScore W3202060937C103272765 @default.
• W3202060937 hasConceptScore W3202060937C105569014 @default.
• W3202060937 hasConceptScore W3202060937C120882062 @default.
• W3202060937 hasConceptScore W3202060937C120991184 @default.
• W3202060937 hasConceptScore W3202060937C121332964 @default.
• W3202060937 hasConceptScore W3202060937C127313418 @default.
• W3202060937 hasConceptScore W3202060937C159390177 @default.

• next